Overcome the Brightness and Jitter Noises in Video Inter-Frame Tampering Detection
Abstract
:1. Introduction
2. Related Work
2.1. Methods without Considering Noises
2.2. Methods Considering Noises
3. Preliminaries
3.1. Horn and Schunck (H&S) Method
3.2. Robust Optical Flow Algorithm against Brightness Changes
4. Method
4.1. Algorithm 1: Reduce the Impact of Illumination Changes
Algorithm 1: Reduce the impact of illumination changes |
as threshold selected for peak point, |
. |
Output: store position of suspicious tampering point in S. |
, C = 0 //C is the variable counter for peak point |
do |
then |
7: end if |
8: end for |
11: (a) return FORGED VIDEO |
14: else run Algorithm 2 |
15: end if |
16:else return ORIGINAL VIDEO |
17:end if |
4.2. Algorithm 2 Detects Jittery Video
Algorithm 2: Detection algorithm based on video texture changes fraction |
as threshold selected for peak point |
in Algorithm 1 |
do |
then |
7: end if |
8: end for |
then |
10: (a) return FORGED VIDEO |
12:else return ORIGINAL VIDEO |
13:end if |
4.3. Algorithm 3: Make the Judgement of Video Tamper
Algorithm 3: judgment of video tamper |
Input:suspicious tampering point set in S, the variable counter for peak point C |
do |
do |
: |
6: else: |
: |
10: end if |
11: end if |
12: end for |
13: end for |
5. Evaluation of Optical Flow Computation
5.1. Experimental Setup
5.2. Experimental Results and Analysis
6. Experimental Results and Analysis
6.1. Experimental Data
6.2. Experimental Setup
6.3. Experimental Results
7. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Approaches | Descriptions and Parameter Settings |
---|---|
HS | Classical H&S method, . |
HS + IN | H&S method with Intensity Normalization, . |
HS + BR | H&S method with Brightness Relaxing factor, , and d = 0.35. |
the enhanced OF algorithm | combine HS+BR and intensity normalization. |
Approaches | AAE | Average EPE | Time (s) |
---|---|---|---|
HS | 13.188 | 1.350 | 6.07 |
HS + IN | 7.074 | 0.776 | 6.62 |
HS + BR | 28.497 | 6.631 | 7.08 |
Enhanced algorithm | 4.175 | 0.389 | 8.06 |
Parameters | Methods | ||||
---|---|---|---|---|---|
Ref. [3] | Ref. [6] | Ref. [9] | Ref. [37] | Proposed | |
Consider the illumination noise | No | No | Not validated | Not validated | Yes |
Consider the jitter noise | Not validated | Not validated | Not validated | Not validated | Yes |
Validation by multi-forgery | No | No | No | No | Yes |
Forgery detected | Removal/Insertion/copy-move | Copy-move | Removal/insertion/copy-move | Removal/insertion/copy-move | Removal/insertion/copy-move |
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Pu, H.; Huang, T.; Weng, B.; Ye, F.; Zhao, C. Overcome the Brightness and Jitter Noises in Video Inter-Frame Tampering Detection. Sensors 2021, 21, 3953. https://doi.org/10.3390/s21123953
Pu H, Huang T, Weng B, Ye F, Zhao C. Overcome the Brightness and Jitter Noises in Video Inter-Frame Tampering Detection. Sensors. 2021; 21(12):3953. https://doi.org/10.3390/s21123953
Chicago/Turabian StylePu, Han, Tianqiang Huang, Bin Weng, Feng Ye, and Chenbin Zhao. 2021. "Overcome the Brightness and Jitter Noises in Video Inter-Frame Tampering Detection" Sensors 21, no. 12: 3953. https://doi.org/10.3390/s21123953
APA StylePu, H., Huang, T., Weng, B., Ye, F., & Zhao, C. (2021). Overcome the Brightness and Jitter Noises in Video Inter-Frame Tampering Detection. Sensors, 21(12), 3953. https://doi.org/10.3390/s21123953